Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Multiple Human Tracking Using Particle Filter with Gaussian Process Dynamical Model | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2008 Article ID 969456 10 pages doi 2008 969456 Research Article Multiple Human Tracking Using Particle Filter with Gaussian Process Dynamical Model Jing Wang Yafeng Yin and Hong Man Department of Electrical and Computer Engineering School of Engineering and Science Stevens Institute of Technology Hoboken NJ 07030 USA Correspondence should be addressed to Jing Wang jwang@ Received 1 March 2008 Revised 23 July 2008 Accepted 14 October 2008 Recommended by Stefano Tubaro We present a particle filter-based multitarget tracking method incorporating Gaussian process dynamical model GPDM to improve robustness in multitarget tracking. With the particle filter Gaussian process dynamical model PFGPDM a highdimensional target trajectory dataset of the observation space is projected to a low-dimensional latent space in a nonlinear probabilistic manner which will then be used to classify object trajectories predict the next motion state and provide Gaussian process dynamical samples for the particle filter. In addition Histogram-Bhattacharyya GMM Kullback-Leibler and the rotation invariant appearance models are employed respectively and compared in the particle filter as complimentary features to coordinate data used in GPDM. The simulation results demonstrate that the approach can track more than four targets with reasonable runtime overhead and performance. In addition it can successfully deal with occasional missing frames and temporary occlusion. Copyright 2008 Jing Wang et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION Multitarget tracking is an important issue in security applications which have attracted considerable attention and interest in recent years. Some classical approaches to .
